An advanced Ackermann-steered Autonomous Mobile Robot engineered for research, education, industrial automation, and AI-driven robotics development.
Intelligent. Autonomous. Built for Discovery.
Designed at the intersection of robotics, embedded intelligence, and AI perception, the Pantech Autonomous Mobile Robot combines an Ackermann-steered chassis with STM32 real-time motion control, Raspberry Pi 5 edge computing, and NVIDIA Jetson AI acceleration to deliver precise navigation, intelligent perception, and autonomous decision-making for research, education, and industrial automation.
Where autonomous intelligence meets precision robotics ” a platform combining real-time motion control, LiDAR-based navigation, and edge AI perception for research, industrial automation, and next-generation robotics development.
STM32 + FreeRTOS deliver deterministic control of steering, speed, and actuation.
LiDAR-based SLAM, path planning, and obstacle avoidance in dynamic spaces.
Jetson-powered edge AI for detection, tracking, and recognition.
Cycle-accurate actuation tuned for safe, predictable movement.
Five advanced engineering systems working together to deliver smarter, safer, and more autonomous robotic behavior.
STM32-based real-time motion controller running FreeRTOS delivers precise, deterministic control of steering, speed, and actuation.
LiDAR-based SLAM, localization, path planning, and obstacle avoidance enable dependable autonomous navigation.
NVIDIA Jetson-powered perception with TensorRT-optimized deep learning models for detection, tracking, and recognition.
Gazebo digital twin simulation paired with reinforcement learning lets developers train and validate behaviors before deployment.
Modular architecture fuses camera, LiDAR, IMU, and encoder data for robust, expandable robotic perception.
Our layered computing architecture pairs real-time embedded control with edge AI acceleration, engineered to optimize navigation, perception, and autonomous decision-making across every deployment.
Simultaneous localization and mapping builds an accurate real-time model of the robot's surroundings.
Path planning and obstacle avoidance guide the robot safely through dynamic environments.
Deep learning-based perception enables object detection, human detection, and face recognition in real time.
Combining visual and spatial data improves scene understanding and detection reliability.
Simulated environments allow autonomous behaviors to be trained and validated before real-world deployment.
All figures are placeholder values pending verified engineering data and will be updated ahead of launch.
A flexible platform for developing and validating autonomous robotic behaviors.
Learn More
Hands-on learning across embedded systems, robotics, and AI curricula.
Learn More
A platform for developing and testing intelligent perception models.
Learn More
Train and validate autonomous behaviors in simulation before deployment.
Learn More
Prototype autonomous navigation and material movement in warehouse settings.
Learn MoreFrom embedded control and edge computing to AI perception, ROS 2 autonomy, and digital twin simulation, Pantech brings multidisciplinary engineering together to create future-ready autonomous robotics platforms.
STM32, FreeRTOS, motion control
Raspberry Pi 5, Jetson
Vision, TensorRT, sensor fusion
SLAM, navigation, planning
Gazebo, reinforcement learning
Answers to what people most often ask about the Pantech AMR platform.
The Pantech AMR-1 is an Ackermann-steered autonomous mobile robot that combines real-time embedded motion control with edge AI computing, built for research, education, and industrial automation.
The onboard LiDAR continuously scans the surroundings to build a live map of the environment while simultaneously tracking the robot's own position within it, enabling reliable localization and path planning in unfamiliar spaces.
Yes. ROS 2 runs as the core middleware, powering navigation, sensor integration, and communication between the robot's software modules.
A layered compute architecture pairs an STM32-based real-time controller for motion with a Raspberry Pi 5 for robotics tasks and an NVIDIA Jetson module for accelerated AI inference.
Yes. Its perception stack supports real-time object detection, human detection, face recognition, and scene understanding, making it well suited for computer vision and applied AI research.
The platform includes a Gazebo digital twin, allowing behaviors to be trained through reinforcement learning and validated in simulation before deployment on the physical robot.
Yes. The modular hardware architecture allows expansion with additional sensors, manipulators, and pan-tilt mounts alongside the existing camera, LiDAR, IMU, and encoder setup.
Yes. Its open, modular software stack and well-documented hardware make it equally suited to classroom robotics education and more advanced industrial automation research.
Discover how Pantech's Autonomous Mobile Robot platform can accelerate research, education, and industrial automation.
